Editorial Type:
Article Category: Research Article
 | 
Online Publication Date: 01 Jul 2016

BEM-FEM Model for Truck Tire-Pavement Interaction Noise Prediction

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Page Range: 212 – 224
DOI: 10.2346/tire.440301
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ABSTRACT

Tire-pavement interaction noise has become the dominant source of traffic noise for vehicular speeds greater than 30 mph, as the automotive engine and exhaust system noise are being effectively controlled. Compared with field testing for tire-pavement sound pressure measurement, this study develops an efficient boundary element method (BEM)/finite element method (FEM) model for tire-pavement interaction noise prediction for typical truck tires. The tire structure and modal characteristics of a semisteel radial truck tire are computed using the FEM, and the solution for the radiation acoustic fields caused by the vibration under harmonic excitations is based on the BEM. Application of this model is verified for simulation of the noise reduction performance of porous asphalt concrete with different porosity values. These results demonstrate the effectiveness of tire-pavement interaction noise prediction with the BEM/FEM model. Further research will be conducted with the noise excitation resulting from pavement surface texture profiles.

FIG. 1
FIG. 1

Tire mesh. Two-dimensional tire mesh (left) and three-dimensional tire mesh (right).


FIG. 2
FIG. 2

Mesh convergence of vertical contact stress.


FIG. 3
FIG. 3

Mesh convergence of longitudinal contact stress.


FIG. 4
FIG. 4

Comparisons between measured and predicted tire deflections.


FIG. 5
FIG. 5

Comparisons between measured and predicted longitudinal contact stress.


FIG. 6
FIG. 6

Comparisons between measured and predicted transverse contact stress.


FIG. 7
FIG. 7

Example of the acceleration spectrum at tire sidewall.


FIG. 8
FIG. 8

Measurement positions for noise-level evaluation.


FIG. 9
FIG. 9

Sound pressure level at field oints.


FIG. 10
FIG. 10

Overall sound pressure level at different porosities.


Contributor Notes

Corresponding author. Email: hwang.cee@rutgers.edu
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